Many unsupervised learning algorithms make use of kernels that rely on the Euclidean distance between two samples. However, the Euclidean distance is optimal for Gaussian distribut...
Karim T. Abou-Moustafa, Mohak Shah, Fernando De la...
In this paper, we present a new algorithm of snakes with geometric prior. A method of shape alignment using Fourier coefficients is introduced to estimate the Euclidean transform...
Abstract. We propose an original solution for the general reverse k-nearest neighbor (RkNN) search problem in Euclidean spaces. Compared to the limitations of existing methods for ...
We consider the problem of designing a compact communication network that supports efficient routing in an Euclidean plane. Our network design and routing scheme achieves 1+ stret...
- Rate-distortion theory is applied to the problem of joint compression and classification. A Lagrangian distortion measure is used to consider both the squared Euclidean error in ...